Comprehensive Assessment of Existing Copy Move Forgery Detection Discussing the Trends and Challenges

DOI

10.2991/978-94-6463-716-8_42How to use a DOI?

Keywords

Forgery; Deep Learning; RSNET50; VGG; Feature Extraction; Transfer Learning

Abstract

Because of the impactful picture editing instruments, images are available to a few controls; in this manner, their genuineness is becoming problematic particularly when pictures have compelling power, for instance, in an official courtroom, news articles, as well as protection rights. Image forensic approaches decide the trustworthiness of pictures by applying different super advanced mechanisms created in the previous work. In this article, the pictures are broke down for a specific sort of imitation where a locale of a picture is reordered onto a similar picture to make a copying or to hide a few prevailing items. To recognize the copy-move forgery attack, pictures are primary cate-gorized into overlapping square blocks as well as DCT constituents are implemented as the block representations. Because of the great layered feature of the element space, Gaussian RBF kernel PCA is functional to accomplish the condensed dimensional feature vector depiction that likewise superior the proficiency at the time of the feature matching. Investigational trials are conducted to assess the suggested strategy in contrast with cutting edge. Thus, this paper offers the several proposed procedure gives a computationally effective and dependable method of copy-move forgery detection (CMFD) that builds the believability of pictures in proof centered applications.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Varsha Thakur
AU  - Rohit Agarwal
PY  - 2025
DA  - 2025/05/26
TI  - Comprehensive Assessment of Existing Copy Move Forgery Detection Discussing the Trends and Challenges
BT  - Proceedings of the International Conference on Recent Advancements and Modernisations in Sustainable Intelligent Technologies and Applications (RAMSITA 2025)
PB  - Atlantis Press
SP  - 539
EP  - 551
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-716-8_42
DO  - 10.2991/978-94-6463-716-8_42
ID  - Thakur2025
ER  -